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Copilots can suggest the next click, but they rarely deliver the finished job. We dive into a different path: enterprise AI agents that integrate with your systems, understand your business rules, and execute end-to-end workflows with governance, accuracy, and reliability. Rob Bearden co-founder and CEO Sema4.ai shares how their platform moves beyond brittle scripts and UI macros to reasoning-driven automation that adapts to changing contracts, policies, and supply constraints—turning strategy into repeatable, measurable outcomes.
We trace the journey from big data to autonomy: insights and KPIs used to point the way, but humans still had to do the work across dozens of apps and tabs. Agents close that last-mile gap by reading documents, joining data across ERPs and CRMs, and following rule-bound reasoning paths to finish the task. You’ll hear concrete wins like multi-page invoice reconciliation done in minutes with higher accuracy, AP help desk cases resolved without swivel-chair searches, and quote-to-cash automated across fragmented systems. The result is less toil, fewer errors, and outcomes you can audit and scale.
If you’re stuck in AI pilot purgatory, the way out is a platform strategy and tight guardrails. We break down a crawl-walk-run approach: pick a high-leverage use case, define the outcome, run a focused proof, measure ROI, then rinse and repeat. We also scan the broader agent ecosystem—Salesforce, ServiceNow, and hyperscalers are leaning in—while making the case for an enterprise-wide layer that spans SaaS apps, data warehouses, and data lakes. Finance operations lead early adoption, but healthcare, insurance, and manufacturing are close behind, wherever people juggle multiple systems to make a decision.
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